Guided Regularized Random Forest (GRRF) optimization for remote sensing data

  • Emma Izquierdo-Verdiguier (University of Natural Resources and Applied Life Sciences) (Creator)
  • Raul Zurita-Milla (Creator)



Demo of the paper An evaluation of Guided Regularized Random Forest for classification and regression tasks in remote sensing. The code classifies a hyperspectral image using GRRF selection, RF using the same number of features and RF using all features. The authors would like to thank to Houtao Deng for developing the RRF package.
Date made available27 Aug 2021

Cite this